87 citations · 202 across the 51 of their papers we have counts for
12 papers · 1 filter
Astrocyte-Enabled Advancements in Spiking Neural Networks for Large Language Modeling
Guobin Shen, Dongcheng Zhao, Yiting Dong +4
Within the complex neuroarchitecture of the brain, astrocytes play crucial roles in development, structure, and metabolism. These cells regulate neural activity through tripartite…
Is Conventional SNN Really Efficient? A Perspective from Network Quantization
Guobin Shen, Dongcheng Zhao, Tenglong Li +2
Spiking Neural Networks (SNNs) have been widely praised for their high energy efficiency and immense potential. However, comprehensive research that critically contrasts and correl…
FireFly v2: Advancing Hardware Support for High-Performance Spiking Neural Network with a Spatiotemporal FPGA Accelerator
Jindong Li, Guobin Shen, Dongcheng Zhao +2
Spiking Neural Networks (SNNs) are expected to be a promising alternative to Artificial Neural Networks (ANNs) due to their strong biological interpretability and high energy effic…
Enhancing Efficient Continual Learning with Dynamic Structure Development of Spiking Neural Networks
Bing Han, Feifei Zhao, Yi Zeng +2
Children possess the ability to learn multiple cognitive tasks sequentially, which is a major challenge toward the long-term goal of artificial general intelligence. Existing conti…
Learning the Plasticity: Plasticity-Driven Learning Framework in Spiking Neural Networks
Guobin Shen, Dongcheng Zhao, Yiting Dong +3
The evolution of the human brain has led to the development of complex synaptic plasticity, enabling dynamic adaptation to a constantly evolving world. This progress inspires our e…
Bullying10K: A Large-Scale Neuromorphic Dataset towards Privacy-Preserving Bullying Recognition
Yiting Dong, Yang Li, Dongcheng Zhao +2
The prevalence of violence in daily life poses significant threats to individuals' physical and mental well-being. Using surveillance cameras in public spaces has proven effective…
Improving Stability and Performance of Spiking Neural Networks through Enhancing Temporal Consistency
Dongcheng Zhao, Guobin Shen, Yiting Dong +2
Spiking neural networks have gained significant attention due to their brain-like information processing capabilities. The use of surrogate gradients has made it possible to train…
Dive into the Power of Neuronal Heterogeneity
Guobin Shen, Dongcheng Zhao, Yiting Dong +2
The biological neural network is a vast and diverse structure with high neural heterogeneity. Conventional Artificial Neural Networks (ANNs) primarily focus on modifying the weight…
Multi-scale Evolutionary Neural Architecture Search for Deep Spiking Neural Networks
Wenxuan Pan, Feifei Zhao, Guobin Shen +1
Spiking Neural Networks (SNNs) have received considerable attention not only for their superiority in energy efficiency with discrete signal processing but also for their natural s…
An Efficient Knowledge Transfer Strategy for Spiking Neural Networks from Static to Event Domain
Xiang He, Dongcheng Zhao, Yang Li +3
Spiking neural networks (SNNs) are rich in spatio-temporal dynamics and are suitable for processing event-based neuromorphic data. However, event-based datasets are usually less an…
Exploiting High Performance Spiking Neural Networks with Efficient Spiking Patterns
Guobin Shen, Dongcheng Zhao, Yi Zeng
Spiking Neural Networks (SNNs) use discrete spike sequences to transmit information, which significantly mimics the information transmission of the brain. Although this binarized f…
FireFly: A High-Throughput Hardware Accelerator for Spiking Neural Networks with Efficient DSP and Memory Optimization
Jindong Li, Guobin Shen, Dongcheng Zhao +2
Spiking neural networks (SNNs) have been widely used due to their strong biological interpretability and high energy efficiency. With the introduction of the backpropagation algori…